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Connect with us on Social Media! 📸 Instagram: https://www.instagram.com/algorithm_a... 🧵 Threads: https://www.threads.net/@algorithm_av... 📘 Facebook: / algorithmavenue7 🎮 Discord: / discord Code-https://colab.research.google.com/dri... TIME STAMPS: 0:00 - Why and what is pooling? 04:02 - How to apply pooling? 10:37 - Pooling on multiple layers 11:55 - Types of pooling 15:21 - Advantages 16:58 - Disadvantages 18:01 - Code implementation In this video, we dive deep into the Pooling Layer in Convolutional Neural Networks (CNNs) and understand why it is essential in deep learning models. You’ll learn: ✔️ What is a pooling layer in CNN ✔️ Why pooling is used after convolution ✔️ How Max Pooling and Average Pooling work ✔️ Step-by-step intuitive examples ✔️ How pooling reduces computation and overfitting ✔️ Real-world intuition behind pooling operations Pooling layers help CNNs become translation invariant, reduce feature map size, and focus on the most important features in an image. This video explains everything in a beginner-friendly and visual way, perfect for students, beginners, and interview preparation. 📌 Topics Covered: 1.Pooling Layer Basics 2.Max Pooling vs Average Pooling 3.Effect of Pooling on Feature Maps 4.Stride and Kernel Size in Pooling 5.When and where to use pooling in CNNs 👉 If you found this useful, don’t forget to Like , Share , and Subscribe for more awesome content! #PoolingLayer #PoolingOperation #CNN #ConvolutionalNeuralNetwork #CNNArchitecture #MaxPooling #AveragePooling #ImageDownsampling #FeatureExtraction #SpatialReduction #TranslationInvariance #DeepLearning #DeepLearningConcepts #DeepLearningTutorial #CNNBasics #CNNFromScratch #NeuralNetworks #NeuralNetworkLayers #ComputerVision #ComputerVisionBasics #ImageProcessing #MachineLearning #MLTutorial #AI #ArtificialIntelligence #VisionAI #DataScience #AIEducation